Further progress is reported in the system for objective characterization of cells in the human urinary sediment by computer. In additon to 4 previous cell classes for which excellent identifying algorithms have been established, several additional groups of cells were studied with satisfactory discrimination. Initial application of the computer algorithms to visually selected well preserved urothelial cells has been shown to be of diagnostic value in 12 patients. A diagnostic analysis of 13 additional patients is in progress on a small laboratory computer and preliminary results are encouraging. A hierarchiacal analysis of 8 different classes of urothelial cells documented that the cells can be separated into 2 groups, one of which yielded data of diagnostic value. A new method for processing urinary sediment for high resolution scanning has been developed. Further work is in progress in programming small laboratory computer for cell analysis and first attempts at automated full scale analysis of cells in the urinary sediment are planned. The project explores the potential of currently available technology for the cytologic diagnosis of bladder cancer by computer.